您好，欢迎访问安徽省农业科学院 机构知识库！

Comparative study of estimation methods for genomic breeding values

文献类型： 外文期刊

作者： Wang, Chonglong 1 ; Zhang, Qin 2 ; Jiang, Li 2 ; Qian, Rong 1 ; Ding, Xiangdong 2 ; Zhao, Yaofeng 3 ;

作者机构： 1.Anhui Acad Agr Sci, Inst Anim Husb & Vet Med, Hefei 230031, Peoples R China

2.China Agr Univ, Coll Anim Sci & Technol, Minist Agr China, Key Lab Anim Genet Breeding & Reprod, Beijing 100193, Peoples R China

3.China Agr Univ, Coll Biol Sci, Beijing 100193, Peoples R China

关键词： Genomic selection;Estimation of genomic breeding values;Bayesian methods;BLUP methods

期刊名称：SCIENCE BULLETIN （ 影响因子：11.78； 五年影响因子：7.658 ）

ISSN： 2095-9273

年卷期： 2016 年 61 卷 5 期

页码：

收录情况： SCI

摘要： Estimation of genomic breeding values is important in genomic selection. Bayesian and BLUP methods are the main techniques employed. In this study, we conducted a comparative study of BayesA, BayesB, BayesC pi and GBLUP methods in simulated data and real data of Chinese Holstein cattle. Results showed that, in simulated data, the accuracies of all methods were all similarly elevated with the increase of reference population size, but they made different responses to the changes of marker number or QTL number. In real data of Chinese Holstein cattle, BayesA generated the highest accuracy almost for all six traits, and GBLUP performed as well as BayesA for the traits of milk yield, fat yield and protein yield, while for the trait of fat percentage, protein percentage and somatic cell score, three Bayesian methods showed superior to GBLUP. Comprehensively analyzing above results, it can be speculated that accuracies of the three Bayesian methods are not only influenced by the absolute value of QTL number or marker number, but may also be influenced by the ratio of QTL number to marker number. And there is at least one kind of Bayesian methods performing better than GBLUP, when the ratio of QTL number versus marker number is very small or involving large-effect QTL.

  • 相关文献

[1]Bayesian methods for estimating GEBVs of threshold traits. Wang, C-L,Ding, X-D,Wang, J-Y,Liu, J-F,Fu, W-X,Zhang, Z.,Yin, Z-J,Zhang, Q.,Wang, C-L.

[2]Potential of marker selection to increase prediction accuracy of genomic selection in soybean (Glycine max L.). Li, Wenbin,Ma, Yansong,Liu, Zhangxiong,Guo, Yong,Qiu, Lijuan,Ma, Yansong,Luan, Xiaoyan,Reif, Jochen C.,Jiang, Yong,Wen, Zixiang,Wang, Dechun,Han, Tianfu,Wu, Cunxiang,Sun, Shi,Wei, Shuhong,Wang, Shuming,Yang, Chunming,Wang, Huicai,Yang, Chunming,Zhang, Mengchen,Lu, Weiguo,Xu, Ran,Zhou, Rong,Zhou, Xinan,Wang, Ruizhen,Sun, Zudong,Chen, Huaizhu,Zhang, Wanhai,Sun, Bincheng,Wu, Jian,Han, Dezhi,Yan, Hongrui,Hu, Guohua,Liu, Chunyan,Fu, Yashu,Chen, Weiyuan,Guo, Tai,Zhang, Lei,Yuan, Baojun.

作者其他论文 更多>>
置顶
购物车
反馈

© 京ICP备09089781号-29 主办单位：安徽省农业科学院

学术资源： 中国农业科学院 农业专业知识服务系统 农科联盟资源共建共享平台 中国农业科技文献与信息服务平台 中国农业期刊集成服务平台